from sklearn_benchmarks.reporting.hp_match import HPMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = HPMatchReporting("sklearnex", config="config.yml")
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time sklearnex. For instance, a speedup of 2 means that sklearnex is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.000 | NaN | 6.759 | 0.0 | -1 | 1 | NaN | 0.049 | 0.000 | 0.243 | 0.243 | See | See |
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.000 | NaN | 6.757 | 0.0 | -1 | 5 | NaN | 0.048 | 0.000 | 0.246 | 0.246 | See | See |
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.001 | NaN | 6.318 | 0.0 | 1 | 100 | NaN | 0.048 | 0.000 | 0.263 | 0.263 | See | See |
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.000 | NaN | 6.683 | 0.0 | -1 | 100 | NaN | 0.048 | 0.001 | 0.250 | 0.250 | See | See |
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.000 | NaN | 6.788 | 0.0 | 1 | 5 | NaN | 0.048 | 0.001 | 0.243 | 0.243 | See | See |
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.000 | NaN | 6.747 | 0.0 | 1 | 1 | NaN | 0.048 | 0.000 | 0.246 | 0.246 | See | See |
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | NaN | 0.304 | 0.0 | -1 | 1 | NaN | 0.010 | 0.000 | 0.536 | 0.536 | See | See |
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | NaN | 0.318 | 0.0 | -1 | 5 | NaN | 0.010 | 0.000 | 0.513 | 0.513 | See | See |
| 24 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | NaN | 0.316 | 0.0 | 1 | 100 | NaN | 0.010 | 0.000 | 0.525 | 0.525 | See | See |
| 27 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | NaN | 0.319 | 0.0 | -1 | 100 | NaN | 0.010 | 0.001 | 0.495 | 0.496 | See | See |
| 30 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | NaN | 0.325 | 0.0 | 1 | 5 | NaN | 0.010 | 0.000 | 0.505 | 0.505 | See | See |
| 33 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | NaN | 0.320 | 0.0 | 1 | 1 | NaN | 0.010 | 0.000 | 0.499 | 0.499 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.065 | 0.151 | NaN | 0.000 | 0.002 | -1 | 1 | 0.663 | 0.201 | 0.004 | 10.283 | 10.284 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.025 | 0.002 | NaN | 0.000 | 0.025 | -1 | 1 | 1.000 | 0.008 | 0.000 | 3.030 | 3.031 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 3.080 | 0.044 | NaN | 0.000 | 0.003 | -1 | 5 | 0.757 | 0.204 | 0.005 | 15.068 | 15.072 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.029 | 0.006 | NaN | 0.000 | 0.029 | -1 | 5 | 1.000 | 0.009 | 0.001 | 3.254 | 3.263 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.300 | 0.010 | NaN | 0.000 | 0.002 | 1 | 100 | 0.882 | 0.249 | 0.005 | 9.253 | 9.254 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.022 | 0.000 | NaN | 0.000 | 0.022 | 1 | 100 | 1.000 | 0.009 | 0.000 | 2.524 | 2.525 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 3.117 | 0.046 | NaN | 0.000 | 0.003 | -1 | 100 | 0.882 | 0.242 | 0.004 | 12.856 | 12.858 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.024 | 0.002 | NaN | 0.000 | 0.024 | -1 | 100 | 1.000 | 0.008 | 0.001 | 2.855 | 2.869 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.269 | 0.012 | NaN | 0.000 | 0.002 | 1 | 5 | 0.757 | 0.204 | 0.005 | 11.101 | 11.103 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.022 | 0.000 | NaN | 0.000 | 0.022 | 1 | 5 | 1.000 | 0.008 | 0.000 | 2.580 | 2.581 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.240 | 0.007 | NaN | 0.001 | 0.001 | 1 | 1 | 0.663 | 0.201 | 0.002 | 6.178 | 6.178 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.022 | 0.004 | NaN | 0.000 | 0.022 | 1 | 1 | 1.000 | 0.008 | 0.000 | 2.675 | 2.675 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.795 | 0.034 | NaN | 0.000 | 0.002 | -1 | 1 | 0.896 | 0.031 | 0.001 | 57.973 | 57.996 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.005 | 0.001 | NaN | 0.000 | 0.005 | -1 | 1 | 1.000 | 0.001 | 0.000 | 5.750 | 5.772 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.881 | 0.043 | NaN | 0.000 | 0.003 | -1 | 5 | 0.922 | 0.033 | 0.001 | 87.478 | 87.494 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.011 | 0.002 | NaN | 0.000 | 0.011 | -1 | 5 | 1.000 | 0.001 | 0.000 | 13.410 | 13.475 | See | See |
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.181 | 0.007 | NaN | 0.000 | 0.002 | 1 | 100 | 0.929 | 0.078 | 0.002 | 27.843 | 27.853 | See | See |
| 26 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | 1 | 100 | 1.000 | 0.001 | 0.000 | 3.780 | 3.802 | See | See |
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.875 | 0.038 | NaN | 0.000 | 0.003 | -1 | 100 | 0.929 | 0.077 | 0.003 | 37.181 | 37.201 | See | See |
| 29 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.007 | 0.003 | NaN | 0.000 | 0.007 | -1 | 100 | 1.000 | 0.001 | 0.000 | 8.111 | 8.164 | See | See |
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.157 | 0.006 | NaN | 0.000 | 0.002 | 1 | 5 | 0.922 | 0.036 | 0.002 | 60.475 | 60.608 | See | See |
| 32 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | 1 | 5 | 1.000 | 0.001 | 0.000 | 3.924 | 3.929 | See | See |
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.120 | 0.057 | NaN | 0.000 | 0.001 | 1 | 1 | 0.896 | 0.034 | 0.001 | 33.266 | 33.299 | See | See |
| 35 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | 1 | 1 | 1.000 | 0.001 | 0.000 | 2.402 | 2.409 | See | See |
KNeighborsClassifier_kd_tree¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.418 | 0.048 | NaN | 0.023 | 0.0 | -1 | 1 | NaN | 0.858 | 0.089 | 3.982 | 4.004 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.132 | 0.063 | NaN | 0.019 | 0.0 | -1 | 5 | NaN | 0.805 | 0.014 | 5.135 | 5.136 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.962 | 0.074 | NaN | 0.020 | 0.0 | 1 | 100 | NaN | 0.812 | 0.019 | 4.880 | 4.881 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.117 | 0.058 | NaN | 0.019 | 0.0 | -1 | 100 | NaN | 0.837 | 0.049 | 4.919 | 4.927 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.203 | 0.057 | NaN | 0.019 | 0.0 | 1 | 5 | NaN | 0.774 | 0.008 | 5.432 | 5.432 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.154 | 0.092 | NaN | 0.019 | 0.0 | 1 | 1 | NaN | 0.808 | 0.016 | 5.143 | 5.144 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.001 | NaN | 0.019 | 0.0 | -1 | 1 | NaN | 0.003 | 0.002 | 0.249 | 0.283 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.026 | 0.0 | -1 | 5 | NaN | 0.002 | 0.002 | 0.282 | 0.344 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.026 | 0.0 | 1 | 100 | NaN | 0.001 | 0.001 | 0.444 | 0.594 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.026 | 0.0 | -1 | 100 | NaN | 0.001 | 0.000 | 0.608 | 0.608 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.027 | 0.0 | 1 | 5 | NaN | 0.001 | 0.000 | 0.530 | 0.542 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.027 | 0.0 | 1 | 1 | NaN | 0.001 | 0.000 | 0.615 | 0.617 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.855 | 1.003 | NaN | 0.000 | 0.001 | -1 | 1 | 0.929 | 0.112 | 0.003 | 7.610 | 7.612 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | NaN | 0.000 | 0.003 | -1 | 1 | 1.000 | 0.000 | 0.000 | 10.108 | 10.342 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.064 | 0.323 | NaN | 0.000 | 0.001 | -1 | 5 | 0.946 | 0.206 | 0.003 | 5.154 | 5.155 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.004 | 0.000 | NaN | 0.000 | 0.004 | -1 | 5 | 1.000 | 0.000 | 0.000 | 7.518 | 7.805 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 5.744 | 0.437 | NaN | 0.000 | 0.006 | 1 | 100 | 0.951 | 0.615 | 0.010 | 9.335 | 9.337 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.004 | 0.001 | NaN | 0.000 | 0.004 | 1 | 100 | 1.000 | 0.001 | 0.000 | 4.336 | 4.456 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 3.477 | 0.282 | NaN | 0.000 | 0.003 | -1 | 100 | 0.951 | 0.601 | 0.012 | 5.783 | 5.784 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.006 | 0.001 | NaN | 0.000 | 0.006 | -1 | 100 | 1.000 | 0.001 | 0.000 | 6.566 | 6.740 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.781 | 0.320 | NaN | 0.000 | 0.002 | 1 | 5 | 0.946 | 0.207 | 0.004 | 8.603 | 8.605 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | 1 | 5 | 1.000 | 0.000 | 0.000 | 3.393 | 3.493 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.988 | 0.291 | NaN | 0.000 | 0.001 | 1 | 1 | 0.929 | 0.113 | 0.002 | 8.779 | 8.780 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 1 | 1.000 | 0.000 | 0.000 | 3.590 | 3.728 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.032 | 0.013 | NaN | 0.000 | 0.000 | -1 | 1 | 0.891 | 0.000 | 0.000 | 67.826 | 71.611 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | -1 | 1 | 1.000 | 0.000 | 0.000 | 30.963 | 32.341 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.028 | 0.001 | NaN | 0.001 | 0.000 | -1 | 5 | 0.911 | 0.001 | 0.000 | 36.746 | 36.768 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.001 | NaN | 0.000 | 0.003 | -1 | 5 | 1.000 | 0.000 | 0.000 | 35.403 | 37.263 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.042 | 0.007 | NaN | 0.000 | 0.000 | 1 | 100 | 0.894 | 0.005 | 0.000 | 7.855 | 7.855 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 100 | 1.000 | 0.000 | 0.000 | 6.130 | 6.490 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.044 | 0.005 | NaN | 0.000 | 0.000 | -1 | 100 | 0.894 | 0.006 | 0.001 | 7.162 | 7.336 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | -1 | 100 | 1.000 | 0.000 | 0.000 | 20.354 | 21.791 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.023 | 0.000 | NaN | 0.001 | 0.000 | 1 | 5 | 0.911 | 0.001 | 0.000 | 30.305 | 30.406 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 5 | 1.000 | 0.000 | 0.000 | 6.674 | 7.059 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.022 | 0.000 | NaN | 0.001 | 0.000 | 1 | 1 | 0.891 | 0.000 | 0.000 | 47.746 | 47.889 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 1 | 1.000 | 0.000 | 0.000 | 6.841 | 7.183 | See | See |
KMeans_tall¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.615 | 0.125 | 30 | 0.026 | 0.0 | random | NaN | 0.474 | 0.033 | 1.299 | 1.302 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.657 | 0.024 | 30 | 0.024 | 0.0 | k-means++ | NaN | 0.520 | 0.032 | 1.264 | 1.267 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 6.317 | 0.216 | 30 | 0.127 | 0.0 | random | NaN | 2.946 | 0.046 | 2.144 | 2.145 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 6.533 | 0.095 | 30 | 0.122 | 0.0 | k-means++ | NaN | 3.119 | 0.028 | 2.095 | 2.095 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.0 | 30 | 0.009 | 0.000 | random | 0.001 | 0.0 | 0.0 | 8.899 | 13.348 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.0 | 30 | 0.000 | 0.002 | random | 1.000 | 0.0 | 0.0 | 8.646 | 12.981 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.0 | 30 | 0.009 | 0.000 | k-means++ | 0.001 | 0.0 | 0.0 | 10.843 | 11.883 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.0 | 30 | 0.000 | 0.002 | k-means++ | 1.000 | 0.0 | 0.0 | 13.759 | 14.678 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.0 | 30 | 0.378 | 0.000 | random | 0.002 | 0.0 | 0.0 | 7.190 | 7.561 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.0 | 30 | 0.001 | 0.002 | random | 1.000 | 0.0 | 0.0 | 12.765 | 13.106 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.0 | 30 | 0.397 | 0.000 | k-means++ | 0.002 | 0.0 | 0.0 | 6.223 | 6.516 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.0 | 30 | 0.001 | 0.002 | k-means++ | 1.000 | 0.0 | 0.0 | 12.282 | 12.573 | See | See |
KMeans_short¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 0.100 | 0.003 | 20 | 0.002 | 0.0 | random | NaN | 0.034 | 0.002 | 2.922 | 2.927 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 0.267 | 0.005 | 20 | 0.001 | 0.0 | k-means++ | NaN | 0.099 | 0.001 | 2.697 | 2.697 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 0.252 | 0.006 | 20 | 0.032 | 0.0 | random | NaN | 0.142 | 0.004 | 1.779 | 1.780 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 0.725 | 0.020 | 20 | 0.011 | 0.0 | k-means++ | NaN | 0.382 | 0.008 | 1.898 | 1.898 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.007 | 0.000 | random | 0.000 | 0.001 | 0.0 | 3.884 | 3.895 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | random | 1.000 | 0.000 | 0.0 | 12.481 | 13.199 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.007 | 0.000 | k-means++ | 0.001 | 0.001 | 0.0 | 3.783 | 3.806 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | k-means++ | 1.000 | 0.000 | 0.0 | 12.482 | 13.031 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.0 | 20 | 0.266 | 0.000 | random | 0.279 | 0.001 | 0.0 | 2.607 | 2.616 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | random | 1.000 | 0.000 | 0.0 | 9.380 | 9.532 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.0 | 20 | 0.268 | 0.000 | k-means++ | 0.317 | 0.001 | 0.0 | 2.467 | 2.485 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | k-means++ | 1.000 | 0.000 | 0.0 | 8.951 | 9.073 | See | See |
LogisticRegression¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | 11.907 | 0.445 | [20] | 0.067 | 0.000 | NaN | NaN | NaN | NaN | NaN | 2.112 | 0.039 | 5.639 | 5.640 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | 1.007 | 0.604 | [26] | 0.079 | 0.001 | NaN | NaN | NaN | NaN | NaN | 0.850 | 0.040 | 1.185 | 1.186 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 0.000 | 0.0 | [20] | 1.826 | 0.0 | NaN | NaN | NaN | NaN | 0.56 | 0.008 | 0.024 | 0.053 | 0.159 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | 0.000 | 0.0 | [20] | 0.013 | 0.0 | NaN | NaN | NaN | NaN | 1.00 | 0.000 | 0.000 | 0.312 | 0.325 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 0.002 | 0.0 | [26] | 3.970 | 0.0 | NaN | NaN | NaN | NaN | 0.35 | 0.004 | 0.000 | 0.516 | 0.517 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | 0.000 | 0.0 | [26] | 0.845 | 0.0 | NaN | NaN | NaN | NaN | 0.00 | 0.001 | 0.000 | 0.127 | 0.127 | See | See |
Ridge¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | max_iter | random_state | r2_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | 0.206 | 0.005 | NaN | 0.389 | 0.0 | NaN | NaN | NaN | 0.203 | 0.002 | 1.013 | 1.013 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | 1.221 | 0.102 | NaN | 0.655 | 0.0 | NaN | NaN | NaN | 0.353 | 0.280 | 3.456 | 4.412 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | max_iter | random_state | r2_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 0.01 | 0.001 | NaN | 7.810 | 0.0 | NaN | NaN | 0.083 | 0.017 | 0.0 | 0.608 | 0.608 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | 0.00 | 0.000 | NaN | 1.098 | 0.0 | NaN | NaN | NaN | 0.000 | 0.0 | 0.592 | 0.642 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | 0.00 | 0.000 | NaN | 4.764 | 0.0 | NaN | NaN | 1.000 | 0.000 | 0.0 | 0.567 | 0.709 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | 0.00 | 0.000 | NaN | 0.014 | 0.0 | NaN | NaN | NaN | 0.000 | 0.0 | 0.603 | 0.646 | See | See |